def main():
x = [13854, 12213, 11009, 10655, 9503]
x = np.reshape(x, newshape=(5, 1)) / 10000.0
y = [21332, 20162, 19138, 18621, 18016]
y = np.reshape(y, newshape=(5, 1)) / 10000.0
params = []
model = LinearRegression(alpha=0.2, n_iterations=5)
model.x = x
model.y = y
model.n = 5
for i in range(9):
model.optimize()
y_hat = model.model()
params.append((model.a, model.b))
plt.scatter(x, y)
plt.plot(x, y_hat)
plt.savefig(f"{i+1}.png")
plt.cla()
html = """
<html>
<head>
<title>Display</title>
</head>
<body>
"""
for i in range(9):
html += f'<img src="{i+1}.png" /><br />\n'
html += """
</body>
</html>
"""
with open("display.html", "w") as f:
f.write(html)
f.flush()
f.close()
for a, b in params:
print(a, b)
def main():
x = [13854, 12213, 11009, 10655, 9503]
x = np.reshape(x, newshape=(5, 1)) / 10000.0
y = [21332, 20162, 19138, 18621, 18016]
y = np.reshape(y, newshape=(5, 1)) / 10000.0
params = []
model = LinearRegression(alpha=0.2, n_iterations=5)
model.x = x
model.y = y
model.n = 5
for i in range(10):
model.optimize()
y_hat = model.model()
params.append((model.a, model.b))
plt.scatter(x, y)
plt.plot(x, y_hat)
plt.savefig(f"{i+1}.png")
plt.cla()
for a, b in params:
print(a, b)
